metadata

license: apache-2.0
base_model: cross-encoder/nli-roberta-base
tags:
  - generated_from_trainer
datasets:
  - amazon_reviews_multi
metrics:
  - accuracy
model-index:
  - name: nli-roberta-base-finetuned-for-amazon-review-ratings2
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: amazon_reviews_multi
          type: amazon_reviews_multi
          config: en
          split: validation
          args: en
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.55

nli-roberta-base-finetuned-for-amazon-review-ratings2

This model is a fine-tuned version of cross-encoder/nli-roberta-base on the amazon_reviews_multi dataset. It achieves the following results on the evaluation set:

Loss: 1.0153
Meanabsoluteerror: 0.538
Accuracy: 0.55

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Meanabsoluteerror	Accuracy
1.1358	1.0	313	1.0153	0.538	0.55

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3